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LapRegec classification on 2-D data. In red and blue the labeled samples.

 

What is Laplacian Regec?   Learn more...
Supervised classification is one of the most powerful technique to analyze data, when a-priori information is available on the membership of data samples to classes. Unfortunately the labeling process can be both expensive and time-consuming. By exploiting the presence of unlabeled samples, semi-supervised algorithms can produce excellent classification models also when a small amount of labeled data is available. The LapRegec (Laplacian Regec) algorithm is a semi-supervised classifier obtained adding a Laplacian regularization term to Regec. LapRegec produces models that are both accurate and parsimonious in terms of labeled data samples.
 

M. Viola, M. Sangiovanni, G. Toraldo, and Mario R. Guarracino A Laplacian Generalized Eigenvalues Classifier Under submission.

 
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  Acknowledgments

LapReGEC - This is version 1.0 of LapReGEC classification macro for Matlab.

 
This work has been funded by MIUR PON02-00619 projects. Mario Guarracino work has been conducted at National Research Institute University Higher School of Economics and has been supported by the RSF grant n. 14-41-00039.